
import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 			UpperCAmelCase_     (					_A    ,			unittest.TestCase	):


  '''simple docstring'''







  a__       			=						RobertaTokenizer
  a__       			=						RobertaTokenizerFast
  a__       			=						True
  a__       			=						{"""cls_token""": """<s>"""}
  def 				_lowercase				(					self     :					Optional[Any]       )     ->      List[str]:







    """simple docstring"""






    super().setUp()

    # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
    __magic_name__								=			[
        """l""",
        """o""",
        """w""",
        """e""",
        """r""",
        """s""",
        """t""",
        """i""",
        """d""",
        """n""",
        """\u0120""",
        """\u0120l""",
        """\u0120n""",
        """\u0120lo""",
        """\u0120low""",
        """er""",
        """\u0120lowest""",
        """\u0120newer""",
        """\u0120wider""",
        """<unk>""",
    ]
    __magic_name__								=			dict(zip(UpperCamelCase__     ,				range(len(UpperCamelCase__       )       )       )       )
    __magic_name__								=			["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
    __magic_name__								=			{"""unk_token""": """<unk>"""}

    __magic_name__								=			os.path.join(self.tmpdirname     ,				VOCAB_FILES_NAMES["""vocab_file"""]       )
    __magic_name__								=			os.path.join(self.tmpdirname     ,				VOCAB_FILES_NAMES["""merges_file"""]       )
    with open(self.vocab_file     ,				"""w"""     ,				encoding="""utf-8"""       ) as fp:
      fp.write(json.dumps(UpperCamelCase__       ) + """\n"""       )
    with open(self.merges_file     ,				"""w"""     ,				encoding="""utf-8"""       ) as fp:
      fp.write("""\n""".join(UpperCamelCase__       )       )
  def 				_lowercase				(					self     :					Dict     ,				**UpperCamelCase__     :					List[str]       )     ->      List[str]:







    """simple docstring"""






    kwargs.update(self.special_tokens_map       )
    return self.tokenizer_class.from_pretrained(self.tmpdirname     ,				**UpperCamelCase__       )
  def 				_lowercase				(					self     :					str     ,				**UpperCamelCase__     :					str       )     ->      Union[str, Any]:







    """simple docstring"""






    kwargs.update(self.special_tokens_map       )
    return RobertaTokenizerFast.from_pretrained(self.tmpdirname     ,				**UpperCamelCase__       )
  def 				_lowercase				(					self     :					Optional[Any]     ,				UpperCamelCase__     :					Tuple       )     ->      Dict:







    """simple docstring"""






    __magic_name__								=			"""lower newer"""
    __magic_name__								=			"""lower newer"""
    return input_text, output_text
  def 				_lowercase				(					self     :					Any       )     ->      Optional[Any]:







    """simple docstring"""






    __magic_name__								=			self.tokenizer_class(self.vocab_file     ,				self.merges_file     ,				**self.special_tokens_map       )
    __magic_name__								=			"""lower newer"""
    __magic_name__								=			["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
    __magic_name__								=			tokenizer.tokenize(UpperCamelCase__       )  # , add_prefix_space=True)
    self.assertListEqual(UpperCamelCase__     ,				UpperCamelCase__       )

    __magic_name__								=			tokens + [tokenizer.unk_token]
    __magic_name__								=			[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__       )     ,				UpperCamelCase__       )
  def 				_lowercase				(					self     :					str       )     ->      Optional[int]:







    """simple docstring"""






    __magic_name__								=			self.get_tokenizer()

    self.assertListEqual(tokenizer.encode("""Hello world!"""     ,				add_special_tokens=UpperCamelCase__       )     ,				[0, 3_1414, 232, 328, 2]       )
    self.assertListEqual(
        tokenizer.encode("""Hello world! cécé herlolip 418"""     ,				add_special_tokens=UpperCamelCase__       )     ,				[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]     ,				)
  @slow
  def 				_lowercase				(					self     :					Optional[int]       )     ->      List[Any]:







    """simple docstring"""






    __magic_name__								=			self.tokenizer_class.from_pretrained("""roberta-base"""       )

    __magic_name__								=			tokenizer.encode("""sequence builders"""     ,				add_special_tokens=UpperCamelCase__       )
    __magic_name__								=			tokenizer.encode("""multi-sequence build"""     ,				add_special_tokens=UpperCamelCase__       )

    __magic_name__								=			tokenizer.encode(
        """sequence builders"""     ,				add_special_tokens=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__       )
    __magic_name__								=			tokenizer.encode(
        """sequence builders"""     ,				"""multi-sequence build"""     ,				add_special_tokens=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__       )

    __magic_name__								=			tokenizer.build_inputs_with_special_tokens(UpperCamelCase__       )
    __magic_name__								=			tokenizer.build_inputs_with_special_tokens(UpperCamelCase__     ,				UpperCamelCase__       )

    assert encoded_sentence == encoded_text_from_decode
    assert encoded_pair == encoded_pair_from_decode
  def 				_lowercase				(					self     :					Optional[Any]       )     ->      int:







    """simple docstring"""






    __magic_name__								=			self.get_tokenizer()

    __magic_name__								=			"""Encode this sequence."""
    __magic_name__								=			tokenizer.byte_encoder[""" """.encode("""utf-8"""       )[0]]

    # Testing encoder arguments
    __magic_name__								=			tokenizer.encode(UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__       )
    __magic_name__								=			tokenizer.convert_ids_to_tokens(encoded[0]       )[0]
    self.assertNotEqual(UpperCamelCase__     ,				UpperCamelCase__       )

    __magic_name__								=			tokenizer.encode(UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__       )
    __magic_name__								=			tokenizer.convert_ids_to_tokens(encoded[0]       )[0]
    self.assertEqual(UpperCamelCase__     ,				UpperCamelCase__       )

    tokenizer.add_special_tokens({"""bos_token""": """<s>"""}       )
    __magic_name__								=			tokenizer.encode(UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
    __magic_name__								=			tokenizer.convert_ids_to_tokens(encoded[1]       )[0]
    self.assertNotEqual(UpperCamelCase__     ,				UpperCamelCase__       )

    # Testing spaces after special tokens
    __magic_name__								=			"""<mask>"""
    tokenizer.add_special_tokens(
        {"""mask_token""": AddedToken(UpperCamelCase__     ,				lstrip=UpperCamelCase__     ,				rstrip=UpperCamelCase__       )}       )  # mask token has a left space
    __magic_name__								=			tokenizer.convert_tokens_to_ids(UpperCamelCase__       )

    __magic_name__								=			"""Encode <mask> sequence"""
    __magic_name__								=			"""Encode <mask>sequence"""

    __magic_name__								=			tokenizer.encode(UpperCamelCase__       )
    __magic_name__								=			encoded.index(UpperCamelCase__       )
    __magic_name__								=			tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]       )[0]
    self.assertEqual(UpperCamelCase__     ,				UpperCamelCase__       )

    __magic_name__								=			tokenizer.encode(UpperCamelCase__       )
    __magic_name__								=			encoded.index(UpperCamelCase__       )
    __magic_name__								=			tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]       )[0]
    self.assertNotEqual(UpperCamelCase__     ,				UpperCamelCase__       )
  def 				_lowercase				(					self     :					Optional[int]       )     ->      Any:







    """simple docstring"""






    pass
  def 				_lowercase				(					self     :					Union[str, Any]       )     ->      Dict:







    """simple docstring"""






    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
      with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(UpperCamelCase__     ,				**UpperCamelCase__       )
        __magic_name__								=			self.tokenizer_class.from_pretrained(UpperCamelCase__     ,				**UpperCamelCase__       )
        __magic_name__								=			"""A, <mask> AllenNLP sentence."""
        __magic_name__								=			tokenizer_r.encode_plus(UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__     ,				return_token_type_ids=UpperCamelCase__       )
        __magic_name__								=			tokenizer_p.encode_plus(UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__     ,				return_token_type_ids=UpperCamelCase__       )

        # token_type_ids should put 0 everywhere
        self.assertEqual(sum(tokens_r["""token_type_ids"""]       )     ,				sum(tokens_p["""token_type_ids"""]       )       )

        # attention_mask should put 1 everywhere, so sum over length should be 1
        self.assertEqual(
            sum(tokens_r["""attention_mask"""]       ) / len(tokens_r["""attention_mask"""]       )     ,				sum(tokens_p["""attention_mask"""]       ) / len(tokens_p["""attention_mask"""]       )     ,				)

        __magic_name__								=			tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]       )
        __magic_name__								=			tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]       )

        # Rust correctly handles the space before the mask while python doesnt
        self.assertSequenceEqual(tokens_p["""input_ids"""]     ,				[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]       )
        self.assertSequenceEqual(tokens_r["""input_ids"""]     ,				[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]       )

        self.assertSequenceEqual(
            UpperCamelCase__     ,				["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]       )
        self.assertSequenceEqual(
            UpperCamelCase__     ,				["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]       )
  def 				_lowercase				(					self     :					Any       )     ->      List[Any]:







    """simple docstring"""






    for trim_offsets, add_prefix_space in itertools.product([True, False]     ,				repeat=2       ):
      __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
          self.tmpdirname     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )

      __magic_name__								=			json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()       )
      __magic_name__								=			json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()       )

      self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]     ,				UpperCamelCase__       )

      self.assertEqual(post_processor_state["""add_prefix_space"""]     ,				UpperCamelCase__       )
      self.assertEqual(post_processor_state["""trim_offsets"""]     ,				UpperCamelCase__       )





  def 				_lowercase				(					self     :					List[Any]       )     ->      List[Any]:







    """simple docstring"""






    for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
      with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
        __magic_name__								=			"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
        __magic_name__								=			F'''{text_of_1_token} {text_of_1_token}'''

        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
            UpperCamelCase__     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )
        __magic_name__								=			tokenizer_r(UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
        self.assertEqual(encoding.offset_mapping[0]     ,				(0, len(UpperCamelCase__       ))       )
        self.assertEqual(
            encoding.offset_mapping[1]     ,				(len(UpperCamelCase__       ) + 1, len(UpperCamelCase__       ) + 1 + len(UpperCamelCase__       ))     ,				)

        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
            UpperCamelCase__     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )
        __magic_name__								=			tokenizer_r(UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
        self.assertEqual(encoding.offset_mapping[0]     ,				(0, len(UpperCamelCase__       ))       )
        self.assertEqual(
            encoding.offset_mapping[1]     ,				(len(UpperCamelCase__       ) + 1, len(UpperCamelCase__       ) + 1 + len(UpperCamelCase__       ))     ,				)

        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
            UpperCamelCase__     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )
        __magic_name__								=			tokenizer_r(UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
        self.assertEqual(encoding.offset_mapping[0]     ,				(0, len(UpperCamelCase__       ))       )
        self.assertEqual(
            encoding.offset_mapping[1]     ,				(len(UpperCamelCase__       ), len(UpperCamelCase__       ) + 1 + len(UpperCamelCase__       ))     ,				)

        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
            UpperCamelCase__     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )
        __magic_name__								=			tokenizer_r(UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
        self.assertEqual(encoding.offset_mapping[0]     ,				(0, len(UpperCamelCase__       ))       )
        self.assertEqual(
            encoding.offset_mapping[1]     ,				(len(UpperCamelCase__       ), len(UpperCamelCase__       ) + 1 + len(UpperCamelCase__       ))     ,				)

        __magic_name__								=			F''' {text}'''

        # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
        #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
        # )
        # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
        # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
        # self.assertEqual(
        #     encoding.offset_mapping[1],
        #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
        # )

        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
            UpperCamelCase__     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )
        __magic_name__								=			tokenizer_r(UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
        self.assertEqual(encoding.offset_mapping[0]     ,				(1, 1 + len(UpperCamelCase__       ))       )
        self.assertEqual(
            encoding.offset_mapping[1]     ,				(1 + len(UpperCamelCase__       ) + 1, 1 + len(UpperCamelCase__       ) + 1 + len(UpperCamelCase__       ))     ,				)

        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
            UpperCamelCase__     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )
        __magic_name__								=			tokenizer_r(UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
        self.assertEqual(encoding.offset_mapping[0]     ,				(0, 1 + len(UpperCamelCase__       ))       )
        self.assertEqual(
            encoding.offset_mapping[1]     ,				(1 + len(UpperCamelCase__       ), 1 + len(UpperCamelCase__       ) + 1 + len(UpperCamelCase__       ))     ,				)

        __magic_name__								=			self.rust_tokenizer_class.from_pretrained(
            UpperCamelCase__     ,				use_fast=UpperCamelCase__     ,				add_prefix_space=UpperCamelCase__     ,				trim_offsets=UpperCamelCase__       )
        __magic_name__								=			tokenizer_r(UpperCamelCase__     ,				return_offsets_mapping=UpperCamelCase__     ,				add_special_tokens=UpperCamelCase__       )
        self.assertEqual(encoding.offset_mapping[0]     ,				(0, 1 + len(UpperCamelCase__       ))       )
        self.assertEqual(
            encoding.offset_mapping[1]     ,				(1 + len(UpperCamelCase__       ), 1 + len(UpperCamelCase__       ) + 1 + len(UpperCamelCase__       ))     ,				)



# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase     :	Tuple       			=  {'configuration_timm_backbone': ['TimmBackboneConfig']}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCAmelCase     :	str       			=  ['TimmBackbone']


if TYPE_CHECKING:
    from .configuration_timm_backbone import TimmBackboneConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_timm_backbone import TimmBackbone

else:
    import sys

    __lowerCAmelCase     :	str       			=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

